backend creating bar chart for hourly avg aqi values

backend/flask/app/graph_pm.py

@@ -80,9 +80,9 @@ def build_pm_plot(x, y, y_max, thresh, title):
     plt.figure()
 
 
-
 def rebuild_pm_bar(config):
-    """ rebuild pm2.5 and pm10 values """
+    """ main function to rebuild pm2.5 and pm10 values """
+    # get data
     rows = get_pm_data(config)
     x, y_1, y_2 = get_pm_axis(rows)
     # max
@@ -93,3 +93,89 @@ def rebuild_pm_bar(config):
     build_pm_plot(x, y_2, y_max, thresh=50, title='10')
     # done
     print('recreated PM 2.5 and PM 10 graphs')
+
+
+# hour bar chart
+def get_hour_data(config):
+    """ get last three days worth of data from postgres """
+    # time
+    now = datetime.now()
+    day_until = int(now.date().strftime('%s'))
+    day_from = day_until - 3 * 24 * 60 * 60
+    # call db
+    conn, cur = db_connect(config)
+    cur.execute(
+        f'SELECT epoch_time, aqi_value FROM aqi \
+        WHERE epoch_time > {day_from} \
+        AND epoch_time < {day_until} \
+        ORDER BY epoch_time DESC;'
+    )
+    rows = cur.fetchall()
+    db_close(conn, cur)
+    return rows
+
+
+def get_hour_axis(rows):
+    """ build x and y from the rows """
+    x_timeline = [datetime.fromtimestamp(i[0]) for i in rows]
+    y_aqi_values = [int(i[1]) for i in rows]
+    # build dataframe
+    data = {'timestamp': x_timeline, 'aqi': y_aqi_values}
+    df = pd.DataFrame(data)
+    indexed = df.set_index('timestamp')
+    indexed.sort_values(by=['timestamp'], inplace=True)
+    mean = indexed.resample('1h').mean()
+    # regroup by hour
+    mean_hour = mean.groupby([mean.index.hour]).mean()
+    mean_hour.reset_index(level=0, inplace=True)
+    # set axis
+    x = mean_hour['timestamp']
+    y = mean_hour['aqi'].round()
+    return x, y
+
+
+def build_hour_plot(x, y):
+    """ takes x and y and writes plot to file """
+    plt_title = 'Last three days average AQI for each hour'
+    # ticks
+    x_range = np.arange(0, 24, step=3)
+    x_hours = [str(i).zfill(2) + ":00" for i in x_range]
+    y_max = np.ceil(max(y)/50) * 50 + 50
+    # color the columns
+    col = []
+    for val in y:
+        if val <= 50:
+            # good
+            col.append('#85a762')
+        elif val > 50 and val <= 100:
+            # moderate
+            col.append('#d4b93c')
+        elif val > 100 and val <= 150:
+            # ufsg
+            col.append('#e96843')
+        elif val > 150 and val <= 200:
+            # unhealthy
+            col.append('#d03f3b')
+        elif val > 200 and val <= 300:
+            # vunhealthy
+            col.append('#be4173')
+        else:
+            # hazardous
+            col.append('#714261')
+    # create plot
+    plt.style.use('seaborn')
+    plt.bar(x, y, color=col, width=0.5)
+    plt.yticks(np.arange(0, y_max, step=50))
+    plt.xticks(ticks=x_range, labels=x_hours)
+    plt.title(plt_title, fontsize=20)
+    plt.tight_layout()
+    plt.savefig('dyn/hours.png', dpi=300)
+    plt.close('all')
+    plt.figure()
+
+
+def rebuild_hour_bar(config):
+    """ main function to rebuild houly bar avg """
+    rows = get_hour_data(config)
+    x, y = get_hour_axis(rows)
+    build_hour_plot(x, y)

backend/flask/app/views.py

@@ -42,6 +42,8 @@ graph.create_current(config)
 graph_pm.rebuild_pm_bar(config)
 graph.rebuild_3days(config)
 graph.rebuild_7days(config)
+graph_pm.rebuild_hour_bar(config)
+
 # build username / pw dict for basic auth
 USER_DATA = {}
 USER_DATA[config['authUsername']] = config['authPassword']
@@ -64,6 +66,9 @@ scheduler.add_job(
 scheduler.add_job(
     graph_pm.rebuild_pm_bar, args=[config], trigger="cron", day='*', hour='1', minute='3', name='pm_bar'
 )
+scheduler.add_job(
+    graph_pm.rebuild_hour_bar, args=[config], trigger="cron", day='*', hour='1', minute='4', name='hour_bar'
+)
 scheduler.start()